Development and validation of a nomogram for catheter-related thrombosis prediction in children with central venous

Wangfang Xie1, Bin Xu2, Xiaofang Lou3

  • 1Comprehensive Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310003, Zhejiang, China.

BMC Pediatrics
|August 20, 2024
PubMed

Insights

A new prediction model helps identify children at risk for catheter-related thrombosis (CRT) using central venous catheters (CVCs). This tool uses factors like catheter duration, sex, and underlying conditions to predict CRT risk in pediatric patients.

Area of Science:

  • Pediatric Thrombosis
  • Vascular Access Devices
  • Clinical Prediction Models

Background:

  • Catheter-related thrombosis (CRT) is a complication of central venous catheters (CVCs) in children.
  • Existing risk factors for CRT in children lack predictive tools or nomograms.
  • This study aimed to develop and validate a predictive model for asymptomatic CRT in pediatric patients with CVCs.

Purpose of the Study:

  • To develop and validate a prediction model for asymptomatic catheter-related thrombosis (CRT) in pediatric patients with central venous catheters (CVCs).

Main Methods:

  • Retrospective observational study of pediatric patients receiving CVCs.
  • Inclusion criteria: consecutive patients admitted between October and December 2021.
  • Development and validation of a logistic regression-based prediction model and nomogram.

Main Results:

  • The study included 669 pediatric patients (553 training, 116 validation).
  • Independent predictors for CRT included catheter time, male sex, congenital heart disease, postoperative status, and femoral CVC placement.
  • The developed nomogram demonstrated good discrimination (AUC=0.77) and calibration in the validation set.

Conclusions:

  • A novel prediction model for CRT in children with CVCs was successfully established.
  • The nomogram incorporates key clinical variables and shows favorable predictive performance.
  • This tool can aid in identifying pediatric patients at risk for CVC-related thrombosis.
Abstract